The field of artificial intelligence is seeing the increased application of satellite imagery to
analyse poverty in its various manifestations. This nascent but rapidly growing intersection of …

Energy poverty affects billions worldwide, including people in developed and develo**
countries. Identifying those living in energy poverty and implementing successful solutions …

China has launched a series of ambitious poverty alleviation strategies to end extreme
poverty, officially announcing the achievement of this goal in 2020. Currently, these counties …

This study proposes a novel approach to provide a more granular poverty map in terms of
coverage (up to a grid level with the spatial resolution of 1.5 km) with less cost and time to …

China shares its board with one developed and thirteen develo** countries. A timely,
precise, and efficient socioeconomic study of border regions is vital for evaluating political …

Poverty is a social issue of global concern. Although socioeconomic indicators can easily
reflect poverty status, the coarse statistical scales and poor timeliness have limited their …

This study introduced a new approach for monitoring regional development by applying
satellite data with machine learning algorithms. Satellite data that represent physical …

Abstract Machine Learning (ML) has rapidly advanced as a transformative tool across
numerous fields, offering new avenues for addressing poverty-related challenges. This study …

This paper presents a methodology to estimate the multidimensional poverty index using
spatial data at the street block level. The data used in this study were obtained from Open …

Human activities in the ocean have never been chronically and continuously investigated on
a large scale. Night-time light (NTL) images collected by the Defense Meteorological …